The invention discloses a multi-
source data fusion-based
air volume dynamic adjustment method of a
fume hood for a
clean environment, particularly relates to the technical field of
clean environment control, and aims at solving the problem that
air volume adjustment of an existing
fume hood cannot give consideration to front air suction safety,
pressure difference stability and overall
energy conservation. A basic operation
data set is formed by collecting and filtering
window opening and cabinet air speed, an
air volume demand value and an initial priority parameter are calculated according to the
data set and a room use state mark to form a demand
data set, and a deviation memory parameter and a fluctuation influence parameter are calculated by fusing room
pressure difference data and the availability of an exhaust fan. Obtaining a stable control priority adjustment coefficient through a time decay
score learning model, correcting the priority, distributing the target exhaust air rate and the exhaust fan output, forming a
target distribution result, comparing the
target distribution result with the actual air
valve opening degree and the exhaust fan output state, calculating the adjustment amount, and issuing a control instruction according to the priority; and the deviation
record feedback updating coefficient and the demand value are verified in the
control period to realize self-adaptive adjustment.